{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>GDP_per_capita</th>\n",
       "      <th>population_total</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>2015</td>\n",
       "      <td>39101.746890</td>\n",
       "      <td>9154302.0</td>\n",
       "      <td>77.484244</td>\n",
       "      <td>Middle East &amp; North Africa (all income levels)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2015</td>\n",
       "      <td>584.025902</td>\n",
       "      <td>33736494.0</td>\n",
       "      <td>63.298195</td>\n",
       "      <td>South Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>2015</td>\n",
       "      <td>13566.905410</td>\n",
       "      <td>99923.0</td>\n",
       "      <td>76.075634</td>\n",
       "      <td>Latin America &amp; Caribbean (all income levels)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Albania</td>\n",
       "      <td>2015</td>\n",
       "      <td>3954.022783</td>\n",
       "      <td>2880703.0</td>\n",
       "      <td>78.203146</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Armenia</td>\n",
       "      <td>2015</td>\n",
       "      <td>3609.654776</td>\n",
       "      <td>2916950.0</td>\n",
       "      <td>74.206195</td>\n",
       "      <td>Europe &amp; Central Asia (all income levels)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                country  year  GDP_per_capita  population_total  \\\n",
       "0  United Arab Emirates  2015    39101.746890         9154302.0   \n",
       "1           Afghanistan  2015      584.025902        33736494.0   \n",
       "2   Antigua and Barbuda  2015    13566.905410           99923.0   \n",
       "3               Albania  2015     3954.022783         2880703.0   \n",
       "4               Armenia  2015     3609.654776         2916950.0   \n",
       "\n",
       "   life_expectancy                                          region  \n",
       "0        77.484244  Middle East & North Africa (all income levels)  \n",
       "1        63.298195                                      South Asia  \n",
       "2        76.075634   Latin America & Caribbean (all income levels)  \n",
       "3        78.203146       Europe & Central Asia (all income levels)  \n",
       "4        74.206195       Europe & Central Asia (all income levels)  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "indicator2 = pd.read_csv('indicator2.csv')\n",
    "indicator2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1e35e711390>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aG2FDwzLigyDVssSXYw3iT8d8QdDsGOi1FTQj/PmYL6P31PRul4Pa1lYl0ra+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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e35d661978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.set_context(\"notebook\", font_scale=1.1)\n",
    "sns.set_style(\"ticks\")\n",
    "\n",
    "# Create scatterplot of dataframe\n",
    "sns.lmplot('GDP_per_capita', # Horizontal axis\n",
    "           'life_expectancy', # Vertical axis\n",
    "           data=indicator2, # Data source\n",
    "           fit_reg=False, # Don't fix a regression line\n",
    "           hue=\"region\", # Set color\n",
    "           scatter_kws={\"marker\": \"D\", # Set marker style\n",
    "                        \"s\": 150}) # S marker size\n",
    "\n",
    "# Set title\n",
    "plt.title('GDP per Capita vs. Life Expectancy')\n",
    "\n",
    "# Set x-axis label\n",
    "plt.xlabel('GDP per Capita(USD)')\n",
    "\n",
    "# Set y-axis label\n",
    "plt.ylabel('Life Expectancy(years)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x151b230c8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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LSZmHy02QhBBCiJtRpSdIv/32G506dSIwsGiC69ChQ/nkk0/Q6/83WTglJYWQ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\nERExUUESERERMVFBEhERETH5PyEgzScZ2s7IAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x151b23cf240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "plt.figure(figsize=(10,8))\n",
    "sns.set_context(\"notebook\", font_scale=1.1)\n",
    "sns.set_style(\"ticks\")\n",
    "\n",
    "\n",
    "sizes = [10, 60, 90, 130, 200] \n",
    "marker_size = pd.cut(indicator2['population_total']/1000000, [0, 100, 200, 400, 600, 800], labels=sizes) \n",
    "sns.lmplot('GDP_per_capita', 'life_expectancy', data=indicator2, hue='region', fit_reg=False, scatter_kws={'s':marker_size})\n",
    "plt.title('GPD_per Capita vs. Life Expectancy 2015')\n",
    "plt.xlabel('GDP per Capita(USD)')\n",
    "plt.ylabel('Life Expectancy(years)')\n",
    "plt.ylim((0, 100))\n",
    "plt.savefig('sns.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sn5w5gJ/MWIoq/Hj8AIJBRYQGVT3Fy66CUnJ2F9GtXTLd2qU0dXLiYsXWfVz91AIevuIE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x151b15df518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "indicator2.plot(kind='scatter', x='GDP_per_capita', y='life_expectancy', s = indicator2['population_total']/1000000, \n",
    "                title = 'GDP per Capita vs. Life Expectancy 2015', ylim=(0,90))\n",
    "plt.savefig('base_pandas.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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l5orjV/DixIUvbOvZ5QBV8EXJJuzwy8k+Hm+j1X9U4xlcOD34LERgy1+GlE745xZQeCR2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\nizqYXlUHVp5YlYO7Yfkr9yI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/xzr+1nVWunJQEeG+KwNV5cYbb6Rjx4507tyZ//0vchBi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\nh2gHodFoNBqHaAeh0Wg0Gof8f++jRwrqnoAuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x151b1931b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "groups = indicator2.groupby('region')\n",
    "for name, group in groups:\n",
    "    ax.plot(group.GDP_per_capita, group.life_expectancy, marker='o', linestyle='', ms=10,\n",
    "label=name)\n",
    "ax.legend(numpoints=1)\n",
    "ax.set_ylim((0, 100))\n",
    "plt.ylabel('Life Expectancy(years)')\n",
    "plt.xlabel('GDP per Capita(USD)')\n",
    "plt.title('Life Expectancy vs. GDP per Capita')\n",
    "plt.savefig('base_pandas.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"3570e68c-b6ae-44cb-9142-638cd1ad5874\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      var el = document.getElementById(\"3570e68c-b6ae-44cb-9142-638cd1ad5874\");\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"3570e68c-b6ae-44cb-9142-638cd1ad5874\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3570e68c-b6ae-44cb-9142-638cd1ad5874' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.7.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"3570e68c-b6ae-44cb-9142-638cd1ad5874\").textContent = \"BokehJS is loading...\";\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
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       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
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       "\n",
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       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
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    },
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     "text": [
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      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='37ab0d9b-3d98-49be-b8ef-d68bf481a492', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='658970e2-4761-4170-84e2-d2d4bc7e2130', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='772919c7-a504-4615-89f2-e938d02d8ba8', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='a5321f4d-1bf1-47e6-a82e-0492e4cfcc14', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='d3bc198e-ffad-476b-90f6-18fda891ff18', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='d55c5bbf-46cf-4199-ac1f-bbc1e4f911e6', ...)\n"
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       "\n",
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       "        <div class=\"bk-plotdiv\" id=\"5909c185-5788-4d99-accb-29e1f073d60c\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
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       "      return new Date();\n",
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       "  \n",
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       "      root._bokeh_is_loading = undefined;\n",
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       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      root._bokeh_timeout = Date.now() + 0;\n",
       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
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       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
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       "       \"</code>\\n\"+\n",
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       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
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      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='5da905e8-68ac-49fd-9fc5-66b09dff8287', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='97617405-89d0-4d20-b74f-c33f09aece7e', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='a6dc0505-8da1-4334-90f0-1fe841c27374', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='df907ae3-c42e-4463-866c-a5761225392a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='ed19efa5-19ec-4d43-8afa-df3bfa90ed13', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='27905bb6-2ad0-4eae-9a02-3fb4b22f8407', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='53830e74-34b4-4e15-b8e5-b9508af8d932', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='667f4d94-ea1b-47c8-811b-fbab13001bda', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='7f5e1b08-b2a6-4bfb-8a49-d6111bf43ab3', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='ab9dc872-4084-49eb-9b63-556933246ae1', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='caec3fe1-57c8-4261-a4dc-26fe09fbc99a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='cd73dec3-c86c-485a-9e5f-0e25529e1c52', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='105bc715-15a9-49b7-b159-78d7a8977938', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='19790125-a34c-4357-8f81-af976a3c769e', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='2169b24b-c46f-4b39-b9e1-29739679401a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='623579d3-8bd9-4635-b3ea-dcd3388b0840', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='69853ce2-5687-460f-948c-d5df9261122c', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='70370963-eb51-4340-b7db-dea1c9e5e134', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='92330248-47c7-43b6-8092-95ee3cc7155e', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='2981a810-81f6-49b5-a8ad-ab4e85530d99', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='746e8f52-3f4b-4600-ad65-967deef9e2b1', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='944b2d5d-a155-4418-99d7-bd1ab048f00f', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='9b0d5d48-2125-4df7-a675-79daa6a9fef6', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='9b398b0d-9211-408a-a646-1ab682a11a8a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='b52ca134-fc69-47da-9085-f7f25cf1e757', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='d469e5fc-144d-41a6-b179-79926b24c4e4', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='1e25ad9c-1c74-447b-9b82-b2e489f56cc7', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='4acd9941-f3be-4031-ae93-3b133daa2656', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='59bcfa5c-e3fa-47d2-a120-e3e9a1d03e82', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='6d852c48-fb64-4c03-847d-7233bf298092', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='717728e2-3cd9-4b14-8a2c-b26118ce8788', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='888b8030-e039-483b-8802-d1ece5ac7956', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='a1788b44-29fb-41e7-b16d-1a7c63792cad', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='3d727d5f-90f5-45aa-a733-9ee76b47a4ab', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='4b632d70-ac7c-45a9-ba5e-6c22d411c6ee', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='59d7fb8e-2e10-4f8f-abfc-0325257ad892', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='78eeec8d-7889-49ac-87e9-9ab184bbede4', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='7f8e9cce-bf1e-4d9a-8d76-7a6b3b399983', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='841145e6-fc6c-4a6b-b304-12f55a4668b6', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='92ae8d36-2df1-4971-9f4f-5e02cf501a9b', ...)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='316794cf-bab9-454e-a1f1-49ae529871d5', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='37ab0d9b-3d98-49be-b8ef-d68bf481a492', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='658970e2-4761-4170-84e2-d2d4bc7e2130', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='772919c7-a504-4615-89f2-e938d02d8ba8', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='a5321f4d-1bf1-47e6-a82e-0492e4cfcc14', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='d3bc198e-ffad-476b-90f6-18fda891ff18', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='d55c5bbf-46cf-4199-ac1f-bbc1e4f911e6', ...)\n"
     ]
    }
   ],
   "source": [
    "from bokeh.charts import Scatter, output_notebook, show\n",
    "from bokeh.models import Axis\n",
    "\n",
    "p = Scatter(indicator2, x='GDP_per_capita', y='life_expectancy', color='region',\n",
    "            title=\"GDP per Capita vs. Life Expectancy 2015\", legend=\"bottom_right\",\n",
    "            xlabel=\"GDP per Capita(USD)\", ylabel=\"Life Expectancy(years)\")\n",
    "\n",
    "p.xaxis[0].formatter.use_scientific = False\n",
    "output_notebook()\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.1.0'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly\n",
    "plotly.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7bcfcZ2D6OopuJk2ch5f/h+lr9iDwhVJqOabPUxUmMMsHWmp+IjWFTFVKzbD+7cL0OTsZ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lniZG+JhXnh1+GFEEIIUT4kQBOcuZxN7IlL7E9Ko7alKbUtTWlobYZtLXNMTRS5tzTSr+Vy4WIq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\nhBBCCFHFSIAmhBBCCFHF/D8vm+kEieKRowAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x151b33fde80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.lines as mlines\n",
    "import numpy as np\n",
    "indicator2 = pd.read_csv('indicator2.csv')\n",
    "\n",
    "plt.figure(figsize=(10,8))\n",
    "colors = (\"red\", \"green\", \"blue\", \"yellow\", \"orange\", \"black\", \"gray\")\n",
    "\n",
    "def attribute_color(region):\n",
    "    colors = {\n",
    "        'East Asia & Pacific (all income levels)':'red',\n",
    "        'Europe & Central Asia (all income levels)':'green',\n",
    "        'Latin America & Caribbean (all income levels)':'blue',\n",
    "        'Middle East & North Africa (all income levels)':'yellow',\n",
    "        'North America':'orange', \n",
    "        'South Asia':'black', \n",
    "        'Sub-Saharan Africa (all income levels)':'gray'\n",
    "    }\n",
    "    return colors.get(region, 'white')\n",
    "color_region = list()\n",
    "qty_states = len(indicator2['region'])\n",
    " \n",
    "for state in range(qty_states):\n",
    "    color_region.append(attribute_color(indicator2['region'][state]))\n",
    "plt.scatter(x = indicator2['GDP_per_capita'],\n",
    "            y = indicator2['life_expectancy'],\n",
    "            s = indicator2['population_total']/1000000,\n",
    "            c = color_region,\n",
    "            alpha = 0.6)\n",
    "plt.title('GDP per Capita vs. Life Expectancy 2015', fontsize=20)\n",
    "plt.xlabel('GDP per Capita(USD)')\n",
    "plt.ylabel('Life Expectancy(years)')\n",
    "plt.ylim(0, 100)\n",
    "\n",
    "regions = ['East Asia & Pacific (all income levels)', 'Europe & Central Asia (all income levels)', 'Latin America & Caribbean (all income levels)', \n",
    "           'Middle East & North Africa (all income levels)', 'North America', 'South Asia', 'Sub-Saharan Africa (all income levels)']\n",
    "\n",
    " \n",
    "legend1_line2d = list()\n",
    "for step in range(len(colors)):\n",
    "    legend1_line2d.append(mlines.Line2D([0], [0],\n",
    "                                        linestyle='none',\n",
    "                                        marker='o',\n",
    "                                        alpha=0.6,\n",
    "                                        markersize=6,\n",
    "                                        markerfacecolor=colors[step]))\n",
    "legend1 = plt.legend(legend1_line2d,\n",
    "                     regions,\n",
    "                     numpoints=1,\n",
    "                     fontsize=10,\n",
    "                     loc='lower right',\n",
    "                     shadow=True)\n",
    "\n",
    "legend2_line2d = list()\n",
    "legend2_line2d.append(mlines.Line2D([0], [0],\n",
    "                                    linestyle='none',\n",
    "                                    marker='o',\n",
    "                                    alpha=0.6,\n",
    "                                    markersize=np.sqrt(10),\n",
    "                                    markerfacecolor='#D3D3D3'))\n",
    "legend2_line2d.append(mlines.Line2D([0], [0],\n",
    "                                    linestyle='none',\n",
    "                                    marker='o',\n",
    "                                    alpha=0.6,\n",
    "                                    markersize=np.sqrt(100),\n",
    "                                    markerfacecolor='#D3D3D3'))\n",
    "legend2_line2d.append(mlines.Line2D([0], [0],\n",
    "                                    linestyle='none',\n",
    "                                    marker='o',\n",
    "                                    alpha=0.6,\n",
    "                                    markersize=np.sqrt(1000),\n",
    "                                    markerfacecolor='#D3D3D3'))\n",
    " \n",
    "legend2 = plt.legend(legend2_line2d,\n",
    "                     ['1', '10', '100'],\n",
    "                     title='Population (in millions)',\n",
    "                     numpoints=1,\n",
    "                     fontsize=10,\n",
    "                     loc='lower left',\n",
    "                     frameon=False,  # no edges\n",
    "                     labelspacing=3, # increase spacing between labels\n",
    "                     handlelength=5, # increase spacing between objects and text\n",
    "                     borderpad=4     # increase the margins of the legend\n",
    "                    )\n",
    "plt.gca().add_artist(legend1)\n",
    " \n",
    "plt.setp(legend2.get_title(),fontsize=10)\n",
    "plt.savefig('matplotlib.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"d13166b6-190f-4ea1-b8cd-b0fbff3f193d\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      var el = document.getElementById(\"d13166b6-190f-4ea1-b8cd-b0fbff3f193d\");\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"d13166b6-190f-4ea1-b8cd-b0fbff3f193d\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'd13166b6-190f-4ea1-b8cd-b0fbff3f193d' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.7.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"d13166b6-190f-4ea1-b8cd-b0fbff3f193d\").textContent = \"BokehJS is loading...\";\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"d13166b6-190f-4ea1-b8cd-b0fbff3f193d\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"08eb9271-1642-40b4-9569-2b6c29cd9fe4\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(root) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "  \n",
       "    var force = false;\n",
       "  \n",
       "    if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      root._bokeh_onload_callbacks = [];\n",
       "      root._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      root._bokeh_timeout = Date.now() + 0;\n",
       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"08eb9271-1642-40b4-9569-2b6c29cd9fe4\");\n",
       "        if (el != null) {\n",
       "          el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "        }\n",
       "      } else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "  \n",
       "    function run_callbacks() {\n",
       "      try {\n",
       "        root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      }\n",
       "      finally {\n",
       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      root._bokeh_onload_callbacks.push(callback);\n",
       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          root._bokeh_is_loading--;\n",
       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"08eb9271-1642-40b4-9569-2b6c29cd9fe4\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '08eb9271-1642-40b4-9569-2b6c29cd9fe4' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"8a51145d-c185-4a34-822d-9b014658fdaf\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"d94070c7-9ec5-4100-ad80-eff564ae94cc\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b7f89870-0096-4904-a1f6-6b4a5ee937fd\",\"type\":\"BasicTicker\"}},\"id\":\"79b05737-8d76-4382-9503-69158524fd2f\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null},\"id\":\"8a8bff88-fcab-40f4-b911-da2be9ea5d54\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"520e9c14-04b2-422f-961c-1f4c4b522647\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"27b2205f-7d5c-4fbe-9ae8-0d108fbe3728\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"formatter\":{\"id\":\"90f80a39-15c7-402c-b277-0aac0ad3e444\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"d94070c7-9ec5-4100-ad80-eff564ae94cc\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b7f89870-0096-4904-a1f6-6b4a5ee937fd\",\"type\":\"BasicTicker\"}},\"id\":\"166a6544-dfcb-471f-a6a9-0a44d79cd932\",\"type\":\"LinearAxis\"},{\"attributes\":{\"data_source\":{\"id\":\"5ea36be6-b728-4733-8f5f-67f9b1f9259f\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1214b9c7-56a8-4a12-8596-b715d39bb212\",\"type\":\"Circle\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"16d76567-8a5c-44ab-82f1-5c0e8d81379d\",\"type\":\"Circle\"},\"selection_glyph\":null,\"view\":{\"id\":\"0b3f6206-b5b4-4de9-8131-f2defec011d1\",\"type\":\"CDSView\"}},\"id\":\"a57eb868-60ce-4295-9a04-a0a2764a7040\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2737624b-0c9b-45cf-a4b9-e5e7ad59ead3\",\"type\":\"LinearScale\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"d94070c7-9ec5-4100-ad80-eff564ae94cc\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"520e9c14-04b2-422f-961c-1f4c4b522647\",\"type\":\"BasicTicker\"}},\"id\":\"6c5a0ba2-5733-49bc-9e15-5d44fd50b9ae\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"5fb68723-d6ea-4ae9-a951-7f73dd72d22a\",\"type\":\"ResetTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"16ac96e5-7386-438c-9ec9-4c49821a54de\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"source\":{\"id\":\"5ea36be6-b728-4733-8f5f-67f9b1f9259f\",\"type\":\"ColumnDataSource\"}},\"id\":\"0b3f6206-b5b4-4de9-8131-f2defec011d1\",\"type\":\"CDSView\"},{\"attributes\":{\"below\":[{\"id\":\"166a6544-dfcb-471f-a6a9-0a44d79cd932\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"9fd27606-9646-4583-bbfd-bcf6e33a435f\",\"type\":\"LinearAxis\"}],\"renderers\":[{\"id\":\"166a6544-dfcb-471f-a6a9-0a44d79cd932\",\"type\":\"LinearAxis\"},{\"id\":\"79b05737-8d76-4382-9503-69158524fd2f\",\"type\":\"Grid\"},{\"id\":\"9fd27606-9646-4583-bbfd-bcf6e33a435f\",\"type\":\"LinearAxis\"},{\"id\":\"6c5a0ba2-5733-49bc-9e15-5d44fd50b9ae\",\"type\":\"Grid\"},{\"id\":\"16ac96e5-7386-438c-9ec9-4c49821a54de\",\"type\":\"BoxAnnotation\"},{\"id\":\"a57eb868-60ce-4295-9a04-a0a2764a7040\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"c4f82d38-e2b5-4477-bdd0-67bfda1c4b36\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"4728de9c-91c8-4fe0-86ef-c25418c449b8\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"cac1dc8a-ab43-4c16-a30e-9efe5392e9d6\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"8fa6489a-f0a4-4238-98c8-df87279e599a\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"8a8bff88-fcab-40f4-b911-da2be9ea5d54\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"2737624b-0c9b-45cf-a4b9-e5e7ad59ead3\",\"type\":\"LinearScale\"}},\"id\":\"d94070c7-9ec5-4100-ad80-eff564ae94cc\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"c4f82d38-e2b5-4477-bdd0-67bfda1c4b36\",\"type\":\"Title\"},{\"attributes\":{\"overlay\":{\"id\":\"16ac96e5-7386-438c-9ec9-4c49821a54de\",\"type\":\"BoxAnnotation\"}},\"id\":\"bdc9cb7c-1141-4d87-a9a5-6528cab01a73\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"callback\":null},\"id\":\"cac1dc8a-ab43-4c16-a30e-9efe5392e9d6\",\"type\":\"DataRange1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"3ca8412f-1bd7-47af-a127-676bff207fab\",\"type\":\"PanTool\"},{\"id\":\"16458f7c-0c2c-4969-ae66-2d420e8a3b25\",\"type\":\"WheelZoomTool\"},{\"id\":\"bdc9cb7c-1141-4d87-a9a5-6528cab01a73\",\"type\":\"BoxZoomTool\"},{\"id\":\"1e50bc08-cb60-4fd7-9fee-3de58103a794\",\"type\":\"SaveTool\"},{\"id\":\"5fb68723-d6ea-4ae9-a951-7f73dd72d22a\",\"type\":\"ResetTool\"},{\"id\":\"aae3bbc2-8c59-459b-b5f1-bb01c510dc96\",\"type\":\"HelpTool\"}]},\"id\":\"4728de9c-91c8-4fe0-86ef-c25418c449b8\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"8fa6489a-f0a4-4238-98c8-df87279e599a\",\"type\":\"LinearScale\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"size\",\"x\",\"y\",\"fill_color\",\"line_color\"],\"data\":{\"fill_color\":[\"Middle East & North Africa (all income levels)\",\"South Asia\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Europe & Central Asia (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"South Asia\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"North America\",\"East Asia & Pacific (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"South Asia\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"North America\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"NaN\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"East Asia & Pacific (all income levels)\",\"East Asia & Pacific (all income levels)\",\"NaN\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"South Asia\",\"Middle East & North Africa (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Europe & Central Asia (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Middle East & North Africa (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia (all income levels)\",\"East Asia & Pacific (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"NaN\",\"East Asia & Pacific (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"East Asia & Pacific (all income levels)\",\"Middle East & North Africa (all income levels)\",\"Latin America & Caribbean (all income levels)\",\"Europe & Central Asia (all income levels)\",\"South Asia\",\"Sub-Saharan Africa (all income levels)\",\"Sub-Saharan Africa (all income levels)\",\"Europe & Central Asia 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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='012eb5ca-6b56-40f9-b0f1-ad2d3090ee5f', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='510073b3-4baa-4b0b-8102-4929d67fd872', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='5da905e8-68ac-49fd-9fc5-66b09dff8287', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='97617405-89d0-4d20-b74f-c33f09aece7e', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='a6dc0505-8da1-4334-90f0-1fe841c27374', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='df907ae3-c42e-4463-866c-a5761225392a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='ed19efa5-19ec-4d43-8afa-df3bfa90ed13', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='27905bb6-2ad0-4eae-9a02-3fb4b22f8407', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='53830e74-34b4-4e15-b8e5-b9508af8d932', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='667f4d94-ea1b-47c8-811b-fbab13001bda', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='7f5e1b08-b2a6-4bfb-8a49-d6111bf43ab3', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='ab9dc872-4084-49eb-9b63-556933246ae1', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='caec3fe1-57c8-4261-a4dc-26fe09fbc99a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='cd73dec3-c86c-485a-9e5f-0e25529e1c52', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='105bc715-15a9-49b7-b159-78d7a8977938', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='19790125-a34c-4357-8f81-af976a3c769e', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='2169b24b-c46f-4b39-b9e1-29739679401a', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='623579d3-8bd9-4635-b3ea-dcd3388b0840', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='69853ce2-5687-460f-948c-d5df9261122c', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='70370963-eb51-4340-b7db-dea1c9e5e134', ...)\n",
      "E-1010 (CDSVIEW_SOURCE_DOESNT_MATCH): CDSView used by Glyph renderer must have a source that matches the Glyph renderer's data source: GlyphRenderer(id='92330248-47c7-43b6-8092-95ee3cc7155e', ...)\n"
     ]
    }
   ],
   "source": [
    "from bokeh.plotting import figure, output_notebook, show\n",
    "p = figure()\n",
    "p.circle(indicator2['GDP_per_capita'], indicator2['life_expectancy'], size=indicator2['population_total']/100000000, \n",
    "         color=indicator2['region'], alpha=0.5)\n",
    "output_notebook()\n",
    "show(p)"
   ]
  }
 ],
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